Parsimony vs predictive and functional performance of three stomatal optimization principles in a big-leaf framework

Stomatal Parameters in a Changing Environment

We recommend that stomatal slope parameters (g1) be inferred by inversion so that variations in g1 may be attributed to variations physiological and environmental conditions. Understanding g1 will advance predictions of plant gas exchange and performance under global climate.

Generalized Stomatal Optimization of Evolutionary Fitness Proxies for Predicting Plant Gas Exchange Under Drought, Heatwaves, and Elevated CO2

Stomata control plant water loss and photosynthetic carbon gain. Developing more generalized and accurate stomatal models is essential for earth system models and predicting responses under novel environmental conditions associated with global change. Plant optimality theories offer one promising approach, but most such theories assume that stomatal conductance maximizes photosynthetic net carbon assimilation subject to some cost or constraint of water. We move beyond this approach by developing a new, generalized optimality theory of stomatal conductance, optimizing any non-foliar proxy that requires water and carbon reserves, like growth, survival, and reproduction. We overcome two prior limitations. First, we reconcile the computational efficiency of instantaneous optimization with a more biologically meaningful dynamic feedback optimization over plant lifespans. Second, we incorporate non-steady-state physics in the optimization to account for the temporal changes in the water, carbon, and energy storage within a plant and its environment that occur over the timescales that stomata act, contrary to previous theories. Our optimal stomatal conductance compares well to observations from seedlings, saplings, and mature trees from field and greenhouse experiments. Our model predicts predispositions to mortality during the 2018 European drought and captures realistic responses to environmental cues, including the partial alleviation of heat stress by evaporative cooling and the negative effect of accumulating foliar soluble carbohydrates, promoting closure under elevated CO2. We advance stomatal optimality theory by incorporating generalized evolutionary fitness proxies and enhance its utility without compromising its realism, offering promise for future models to more realistically and accurately predict global carbon and water fluxes.

Kinetic factors of physiology and the dynamic light environment influence the economic landscape of short-term hydraulic risk

Optimality-based models of stomatal conductance unify biophysical and evolutionary constraints and can improve predictions of land-atmosphere carbon and water exchange. Recent models incorporate hydraulic constraints by penalizing excessive stomatal opening in relation to hydraulic damage caused by low water potentials. We used simulation models to test whether penalties based solely on vulnerability curves adequately represent the optimality hypothesis, given that they exclude the effects of kinetic factors on stomatal behavior and integrated carbon balance. To quantify the effects of nonsteady-state phenomena on the landscape of short-term hydraulic risk, we simulated diurnal dynamics of leaf physiology for 10 000 patches of leaf in a canopy and used a ray-tracing model, Helios, to simulate realistic variation in sunfleck dynamics. Our simulations demonstrated that kinetic parameters of leaf physiology and sunfleck properties influence the economic landscape of short-term hydraulic risk, as characterized by the effect of stomatal strategy (gauged by the water potential causing a 50% hydraulic penalty) on both aggregated carbon gain and the aggregated carbon cost of short-term hydraulic risk. Hydraulic penalties in optimization models should be generalized to allow their parameters to account for kinetic factors, in addition to parameters of hydraulic vulnerability.

Decomposition rate as an emergent property of optimal microbial foraging

Decomposition kinetics are fundamental for quantifying carbon and nutrient cycling in terrestrial and aquatic ecosystems. Several theories have been proposed to construct process-based kinetics laws, but most of these theories do not consider that microbial decomposers can adapt to environmental conditions, thereby modulating decomposition. Starting from the assumption that a homogeneous microbial community maximizes its growth rate over the period of decomposition, we formalize decomposition as an optimal control problem where the decomposition rate is a control variable. When maintenance respiration is negligible, we find that the optimal decomposition kinetics scale as the square root of the substrate concentration, resulting in growth kinetics following a Hill function with exponent 1/2 (rather than the Monod growth function). When maintenance respiration is important, optimal decomposition is a more complex function of substrate concentration, which does not decrease to zero as the substrate is depleted. With this optimality-based formulation, a trade-off emerges between microbial carbon-use efficiency (ratio of growth rate over substrate uptake rate) and decomposition rate at the beginning of decomposition. In environments where carbon substrates are easily lost due to abiotic or biotic factors, microbes with higher uptake capacity and lower efficiency are selected, compared to environments where substrates remain available. The proposed optimization framework provides an alternative to purely empirical or process-based formulations for decomposition, allowing exploration of the effects of microbial adaptation on element cycling.

Leaf Shedding and Non-Stomatal Limitations of Photosynthesis Mitigate Hydraulic Conductance Losses in Scots Pine Saplings During Severe Drought Stress

During drought, trees reduce water loss and hydraulic failure by closing their stomata, which also limits photosynthesis. Under severe drought stress, other acclimation mechanisms are trigged to further reduce transpiration to prevent irreversible conductance loss. Here, we investigate two of them: the reversible impacts on the photosynthetic apparatus, lumped as non-stomatal limitations (NSL) of photosynthesis, and the irreversible effect of premature leaf shedding. We integrate NSL and leaf shedding with a state-of-the-art tree hydraulic simulation model (SOX+) and parameterize them with example field measurements to demonstrate the stress-mitigating impact of these processes. We measured xylem vulnerability, transpiration, and leaf litter fall dynamics in Pinus sylvestris (L.) saplings grown for 54 days under severe dry-down. The observations showed that, once transpiration stopped, the rate of leaf shedding strongly increased until about 30% of leaf area was lost on average. We trained the SOX+ model with the observations and simulated changes in root-to-canopy conductance with and without including NSL and leaf shedding. Accounting for NSL improved model representation of transpiration, while model projections about root-to-canopy conductance loss were reduced by an overall 6%. Together, NSL and observed leaf shedding reduced projected losses in conductance by about 13%. In summary, the results highlight the importance of other than purely stomatal conductance-driven adjustments of drought resistance in Scots pine. Accounting for acclimation responses to drought, such as morphological (leaf shedding) and physiological (NSL) adjustments, has the potential to improve tree hydraulic simulation models, particularly when applied in predicting drought-induced tree mortality.